Enterprise AI Analysis
The Era of Agentic Organization: Learning to Organize with Language Models
We envision a new era of AI, termed agentic organization, where agents solve complex problems by working collaboratively and concurrently, enabling outcomes beyond individual intelligence. To realize this vision, we introduce asynchronous thinking (AsyncThink) as a new paradigm of reasoning with large language models, which organizes the internal thinking process into concurrently executable structures.
Executive Impact: Key Performance Metrics
AsyncThink demonstrates significant advancements in critical AI performance areas, delivering tangible benefits for enterprise problem-solving.
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Accuracy on Multi-Solution Countdown
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Lower Inference Latency
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Zero-Shot Accuracy on Unseen Sudoku
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
What is Agentic Organization?
Agentic organization refers to an organizational system where multiple AI agents collaborate to solve complex problems, exceeding individual intelligence. This framework enables agents to work collaboratively and concurrently, enhancing problem-solving capabilities in ways individual agents cannot achieve.
Understanding Asynchronous Thinking (AsyncThink)
Asynchronous Thinking (AsyncThink) is a new paradigm for reasoning with large language models that organizes internal thinking processes into concurrently executable structures. It involves an organizer dynamically assigning sub-queries to workers and merging intermediate knowledge, allowing for adaptive and dynamic problem-solving.
The Organizer-Worker Thinking Protocol
The Organizer-Worker Thinking Protocol defines two roles: an organizer that manages the overall thinking process (using Fork and Join actions) and workers that execute individual sub-queries concurrently. Both roles share the same LLM backbone, providing a flexible foundation for exploring diverse execution structures and optimizing thinking efficiency.
Comparison of Thinking Paradigms
AsyncThink learns to form an agentic organization to think concurrently and collaboratively, improving upon traditional sequential and parallel methods.
Sequential Thinking
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Parallel Thinking
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Asynchronous Thinking (Agentic Organization)
Key Performance Improvement
28% Lower Inference Latency Compared to Parallel Thinking| Method | AIME-24 Accuracy (↑) | AIME-24 Latency (↓) | AMC-23 Accuracy (↑) | AMC-23 Latency (↓) |
|---|---|---|---|---|
| Sequential-Thinking-L1K | 24.7 | 1022.6 | 59.5 | 990.0 |
| Sequential-Thinking-L2K | 35.3 | 2048.0 | 67.0 | 2001.1 |
| Parallel-Thinking-L1K | 24.7 | 1024.2 | 61.9 | 1029.5 |
| Parallel-Thinking-L2K | 38.7 | 2048.0 | 72.8 | 2031.4 |
| AsyncThink | 38.7 | 1468.0 | 73.3 | 1459.5 |
Case Study: Multi-Solution Countdown (Figure 8)
AsyncThink demonstrates multistage divide-and-merge reasoning. The organizer adaptively uses workers to explore multiplication-based combinations, merges results, and launches new sub-queries. This iterative Fork-Join process efficiently explores solutions, yielding four distinct valid expressions, showcasing an ability to organize efficient thinking beyond sequential methods.
Achieves broader solution coverage and higher reliability with lower latency than sequential thinking.
Case Study: Mathematical Reasoning (Figure 9)
With an agent pool of c=4, AsyncThink assigns sub-queries to three workers, each exploring a distinct geometric formulation (e.g., coordinate method, alternative coords, unit edge length). Workers run concurrently, derive consistent results (cos θ = 1/3), and then rejoin for verification, converging to a final answer. This highlights the ability to organize multiple thinking paths and leverage intermediate results.
Showcases organized reasoning patterns beyond reflection or self-correction, leveraging intermediate results for further thinking.
Zero-Shot Generalization
89.4% Accuracy on Unseen Sudoku Task (Zero-Shot)Advanced ROI Calculator
Estimate the potential return on investment for integrating Agentic Organization and AsyncThink into your enterprise operations.
Estimated Annual Savings
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Annual Hours Reclaimed
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Implementation Roadmap
Our phased approach ensures a smooth transition to agentic organization, maximizing benefits while minimizing disruption.
Scaling Agentic Organization
Explore scaling agent pools to hundreds or thousands of diverse, specialized workers equipped with external tools (e.g., code interpreters, database query engines, web search APIs), creating a more powerful learning problem for the organizer.
Recursive Agentic Organization
Enable workers to dynamically become sub-organizers, creating flexible, hierarchical structures for multi-level problem decomposition. This supports deeply nested and complex tasks requiring a structured, recursive approach.
Human-AI Agentic Organization
Integrate humans directly into the agentic organization. Humans can act as organizers, dispatching tasks to AI workers, or as workers, delegating tasks requiring human judgment. This fosters collaborative planning and hybridized intelligence.
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